Request for Founders

The world runs on uncertainty. Markets shift in milliseconds, robots navigate chaotic warehouses, patients deteriorate without warning, and critical systems whisper before they fail. Yet most AI still thinks in batch jobs and overnight updates. We're looking for founders ready to build the next generation of companies powered by real-time probabilistic inference — technology that turns uncertainty into competitive advantage.

Your Challenge

Build the next generation of companies powered by real-time probabilistic inference

Our Promise

We'll provide the tools, support, and resources to build the future of probabilistic AI

Your Opportunity

Build the next generation of companies powered by real-time probabilistic inference

Autonomous Systems That Actually Work

Founder Request:
Drone swarms, mobile robots, real-time sensor fusion, warehouse automation

Starting Point Examples:

Drone Dynamics - Complete 3D drone physics with waypoint navigation, motor control, and real-time trajectory optimization
Multi-Agent Trajectory Planning - Sophisticated collision avoidance using halfspace priors, coordinated movement through complex environments
POMDP Control - Decision making under uncertainty with incomplete information
Nonlinear Sensor Fusion - Mars rover localization using beacon triangulation

Commercial Applications: Search & rescue drones, warehouse robotics, defense systems, autonomous vehicle coordination

Financial Systems That Never Sleep

Founder Request:
Streaming risk systems, real-time portfolio optimization, market-speed processing

Starting Point Examples:

Contextual Bandits - Real-time decision making with uncertainty quantification
Infinite Data Stream - Continuous Kalman filtering with streaming data processing
AR/ARMA Models - Time series modeling for financial forecasting
Parameter Optimization - Real-time parameter tuning and optimization

Commercial Applications: HFT systems, risk management platforms, regulatory compliance, algorithmic trading

Security That Sees Everything

Founder Request:
Live Bayesian threat graphs, multi-vector detection, reduced false positives

Starting Point Examples:

Hidden Markov Models - Pattern recognition with unknown system dynamics
Bayesian Networks - Probabilistic reasoning and belief propagation
Streaming Inference - Real-time anomaly detection
Incomplete Data Handling - Robust inference with missing information

Commercial Applications: SOC platforms, MSSP services, network security, fraud detection

Infrastructure That Predicts Itself

Founder Request:
Predictive maintenance, grid optimization, continuous monitoring

Starting Point Examples:

Kalman Filtering - State estimation with missing observations and nonlinear dynamics
Infinite Data Stream - Real-time sensor processing and filtering
Structural Dynamics - System state estimation with unknown inputs
Gaussian Process Regression - Continuous prediction and uncertainty quantification

Commercial Applications: Smart grids, industrial IoT, predictive maintenance, energy optimization

Healthcare That Saves Minutes

Founder Request:
Real-time patient monitoring, sepsis detection, clinical decision support

Starting Point Examples:

Hidden Markov Models - Patient state tracking and deterioration detection
Bayesian Networks - Clinical reasoning and diagnosis support
Streaming Inference - Continuous vital signs monitoring
Hierarchical Gaussian Filter - Multi-level patient monitoring

Commercial Applications: ICU monitoring, emergency department alerts, wearable health devices

Marketing That Reads Minds

Founder Request:
Real-time personalization, trend prediction, behavioral modeling

Starting Point Examples:

Contextual Bandits - Adaptive recommendation systems
Bike Rental Prediction - Demand forecasting with missing data
Mixture Models - User segmentation and clustering
Bayesian Regression - Preference modeling with uncertainty

Commercial Applications: Personalization engines, trend prediction platforms, real-time marketing optimization

Games That Evolve

Founder Request:
Dynamic AI, adaptive NPCs, emergent gameplay

Starting Point Examples:

Active Inference - Reinforcement learning through probabilistic inference
POMDP Control - Decision making under uncertainty
Hidden Markov Models - Player behavior modeling
Multi-Agent Planning - Coordinated NPC behavior

Commercial Applications: Adaptive game AI, multiplayer coordination, procedural content generation

Manufacturing That Never Stops

Founder Request:
Real-time quality control, yield optimization, defect prediction

Starting Point Examples:

Kalman Filtering - Process monitoring and control
Streaming Inference - Continuous quality monitoring
Gaussian Mixture Models - Defect classification and detection
Parameter Optimization - Process parameter tuning

Commercial Applications: Semiconductor manufacturing, automotive quality control, precision manufacturing

Logistics That Sees Tomorrow

Founder Request:
Predictive supply chain, real-time optimization, demand forecasting

Starting Point Examples:

Multi-Agent Planning - Coordinated logistics optimization
Demand Prediction - Real-time demand forecasting
Streaming Data Processing - Continuous supply chain monitoring
Hierarchical Models - Multi-level logistics optimization

Commercial Applications: Last-mile delivery, urban logistics, supply chain optimization

Audio That Adapts

Founder Request:
Real-time acoustic modeling, dynamic audio systems, immersive experiences

Starting Point Examples:

Kalman Filtering - Real-time signal processing and noise reduction
Streaming Inference - Continuous audio processing
Nonlinear Systems - Acoustic environment modeling
Parameter Optimization - Real-time audio parameter tuning

Commercial Applications: Automotive sound systems, pro audio, immersive AR/VR audio

Getting Started